CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

Evaluación del rango de transmisión de LoRa para redes de sensores inalámbricas con LoRaWAN en ambientes forestales

Las redes de bajo consumo y amplia cobertura (LPWAN) como LoRaWAN, proporcionan ventajas para desarrollar sistemas de monitoreo en ambientes forestales debido a su fácil configuración, costo, bajo consumo de energía, y amplia cobertura. En cuanto al área de cobertura, la transmisión en entornos forestales es altamente atenuada por la vegetación y debe caracterizarse para optimizar el número de nodos. Este trabajo propone un análisis empírico del rango de transmisión de LoRa con LoRaWAN en entornos forestales basado en un modelo de pérdidas de trayectoria, utilizando el Indicador de Nivel de Señal Recibida (RSSI) y la Relación Señal a Ruido (SNR). Las mediciones se llevaron a cabo en las márgenes de tres ríos locales ubicados en entornos urbanos, semiurbanos y rurales en la ciudad de Cuenca-Ecuador. De las mediciones se encontró que hay una diferencia de distribución significativa entre los lugares de medición, una alta correlación entre dos orillas de un mismo río, una mayor desviación estándar en las mediciones urbanas y una mayor cobertura en áreas rurales.Low Power Wide Area Networks (LPWAN) such as LoRaWAN, provide several advantages to develop monitoring systems in forested environments due to its simple set-up, low cost, low power consumption, and wide coverage. Regarding the coverage area, the transmission in forested environments is highly attenuated by foliage and must be defined to optimize the number of nodes. This paper proposes an empirical study of LoRa with LoRaWAN transmission range in forest, based on path loss modeling using Received Signal Strength Indicator (RSSI) and Signal to- noise-ratio (SNR). The measurements have been conducted in the riverside of three local rivers located at urban, semi-urban and rural environments in the city of Cuenca-Ecuador. The measurement results found that there is a significant distribution difference between measurement places, a high correlation between two banks of a same river, a higher standard deviation in urban measurements and a larger coverage in rural areas.Ingeniero en Electrónica y TelecomunicacionesCuenc

Artificial neural network performance evaluation for a hybrid power domain orthogonal/non-orthogonal multiple access (OMA/NOMA) system

Next-generation wireless technologies face considerable challenges in terms of providing the required latency and connectivity for new heterogeneous mobile networks. Driven by these problems, this study focuses on increasing user connectivity together with system throughput. For doing so, we propose and evaluate a hybrid machine learning-driven orthogonal/non-orthogonal multiple access (OMA/NOMA) system. In this work, we use an artificial neural network (ANN) to assign an OMA or NOMA access method to each user equipment (UE). As part of this research we also evaluate the accuracy and training time of the three most relevant learning algorithms of ANN (L-M, BFGS, and OSS). The main objective is to increase the sum-rate of the mobile network in the introduced beamforming and mmWave channel environment. Simulation results show up to a $20$ sum-rate average performance increase of the system using the ANN management in contrast to a random non-ANN managed system. The Leveberg-Marquard (L-M) training algorithm is the best overall algorithm for this proposed application as presents the highest accuracy of around $77$ despite 37 minutes of training and lower accuracy of $73$ with approximately 28 seconds of training time.Alicant

Evaluation of LoRaWAN transmission range for wireless sensor networks in riparian forests.

© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. Low power wide area networks (LPWAN) such as long range wide area networks (LoRaWAN), provide several advantages on monitoring systems development in forested environments due to its simple set-up, low cost, low power consumption, and wide coverage. Regarding the coverage area, the transmission in forested environments can be highly attenuated by foliage and must be defined to optimize the number of nodes. This paper discusses an empirical study of LoRa with LoRaWAN transmission range in riparian forests, based on path-loss modeling, using both received signal strength indicator (RSSI) and signal-to-noise-ratio (SNR). The measurements have been conducted in the riparian forest of three local rivers at urban, semi-urban, and rural environments located in the city of Cuenca, Ecuador. The measurement results found that there is a significant distribution difference among measurement places, a high correlation between two banks of the same river, a higher standard deviation in urban measurements and a larger coverage in rural areas.© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. Low power wide area networks (LPWAN) such as long range wide area networks (LoRaWAN), provide several advantages on monitoring systems development in forested environments due to its simple set-up, low cost, low power consumption, and wide coverage. Regarding the coverage area, the transmission in forested environments can be highly attenuated by foliage and must be defined to optimize the number of nodes. This paper discusses an empirical study of LoRa with LoRaWAN transmission range in riparian forests, based on path-loss modeling, using both received signal strength indicator (RSSI) and signal-to-noise-ratio (SNR). The measurements have been conducted in the riparian forest of three local rivers at urban, semi-urban, and rural environments located in the city of Cuenca, Ecuador. The measurement results found that there is a significant distribution difference among measurement places, a high correlation between two banks of the same river, a higher standard deviation in urban measurements and a larger coverage in rural areas.Miam

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study (vol 46, pg 2021, 2022)

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